We consider the impact of fairness requirements on the social efficiency of truthful mechanisms for trade, focusing on Bayesian bilateral-trade settings. Unlike the full information case in which all gains-from-trade can be realized and equally split between the two parties, in the private information setting, equitability has devastating welfare implications (even if only required to hold ex-ante). We thus search for an alternative fairness notion and suggest requiring the mechanism to be KS-fair: it must ex-ante equalize the fraction of the ideal utilities of the two traders. We show that there is always a KS-fair (simple) truthful mechanism with expected gains-from-trade that are half the optimum, but always ensuring any better fraction is impossible (even when the seller value is zero). We then restrict our attention to trade settings with a zero-value seller and a buyer with value distribution that is Regular or MHR, proving that much better fractions can be obtained under these conditions.
We report a comprehensive study of Sperrylite (PtAs2), the main platinum source in natural minerals, as a function of applied pressures up to 150 GPa. While no structural phase transition was detected from pressure-dependent X-ray measurements, the unit cell volume shrinks monotonically with pressure following the third-order Birch-Murnaghan equation of state. The mildly semiconducting behavior found in pure synthesized crystals at ambient pressures becomes more insulating upon increasing applied pressure before metalizing at higher pressures, giving way to the appearance of an abrupt decrease in resistance near 3 K at pressures above 92 GPa consistent with the onset of a superconducing phase. The pressure evolution of the calculated electronic band structure reveals the same physical trend as our transport measurements, with a non-monotonic evolution explained by a hole band that is pushed below the Fermi energy and an electron band that approaches it as a function of pressure, both reaching a touching point suggestive of an excitonic state. A topological Lifshitz transition of the electronic structure and an increase in the density of states may naturally explain the onset of superconductivity in this material
Energy security and energy trade are the cornerstones of global economic and social development. The structural robustness of the international oil trade network (iOTN) plays an important role in the global economy. We integrate the machine learning optimization algorithm, game theory, and utility theory for learning an oil trade decision-making model which contains the benefit endowment and cost endowment of economies in international oil trades. We have reconstructed the network degree, clustering coefficient, and closeness of the iOTN well to verify the effectiveness of the model. In the end, policy simulations based on game theory and agent-based model are carried out in a more realistic environment. We find that the export-oriented economies are more vulnerable to be affected than import-oriented economies after receiving external shocks. Moreover, the impact of the increase and decrease of trade friction costs on the international oil trade is asymmetrical and there are significant differences between international organizations.
Ben-Hur Francisco Cardoso, Eva Yamila da Silva Catela, Guilherme Viegas
et al.
Research on productive structures has shown that economic complexity conditions economic growth. However, little is known about which type of complexity, e.g., export or industrial complexity, matters more for regional economic growth in a large emerging country like Brazil. Brazil exports natural resources and agricultural goods, but a large share of the employment derives from services, non-tradables, and within-country manufacturing trade. Here, we use a large dataset on Brazil's formal labor market, including approximately 100 million workers and 581 industries, to reveal the patterns of export complexity, industrial complexity, and economic growth of 558 micro-regions between 2003 and 2019. Our results show that export complexity is more evenly spread than industrial complexity. Only a few -- mainly developed urban places -- have comparative advantages in sophisticated services. Regressions show that a region's industrial complexity is a significant predictor for 3-year growth prospects, but export complexity is not. Moreover, economic complexity in neighboring regions is significantly associated with economic growth. The results show export complexity does not appropriately depict Brazil's knowledge base and growth opportunities. Instead, promoting the sophistication of the heterogeneous regional industrial structures and development spillovers is a key to growth.
Kewal Singh Rana, Raveena Gupta, Debattam Sarkar
et al.
Large unit cell copper-chalcogenide based minerals with high crystalline anharmonicity have a potential for thermoelectric applications owing to their inherent poor lattice thermal conductivity. Here, the softening of copper-selenium bonding and hence crystal framework plays an important role in superionic conduction and thermal conductivity. We have studied Cu26Nb2Sn6Se32, Cu26Nb2Sn6Se31.5 and Cu26Nb2Sn6Se30Te2 minerals with a strategically tailored anionic disorders. These compounds have p-type degenerate behavior with carrier concentration ranging between 1020 cm-3 at 300 K, high power factor and low lattice thermal conductivity at 640 K. The existence of two low frequency Raman active optical modes associated with soft Cu and Se atoms, three localized Einstein modes in specific heat, suggest high scattering between acoustic and optical branches with very short phonon lifetime less than 1 ps. The excess vibrational density of states at low energies with compressed and flat optical branches strongly hinders the heat transport in these crystalline mineral. Comparatively, Cu26Nb2Sn6Se30Te2 is a promising thermoelectric material because of high crystalline anharmonicity and softening of Cu-Se framework due to heavier tellurium atom.
This study aims to reveal the actual effect of FTAs on South Korea's foreign trade volumes of main export and import products separately. The econometric approach of our study follows the gravity model with a panel dataset of 47 countries that have FTA with South Korea for the years between 2001-2018 by using 2-digit HS (Harmonized System) classification for main export and import goods. The study reveals that even though signing the FTA affects positively the trade volume of South Korea and partner countries, the export of South Korea i s affected positively only f or t he b ase metals & articles products while the import of South Korea increases for mineral products, chemical or allied industries products and machinery & mechanical appliances after the FTAs entered into force. Our findings contribute to the literature by ascertaining a new estimation model and original empirical results for South Korean trade policy makers.
Tatiana V. Slashchilina, I. Shaposhnikov, A. V. Aristov
et al.
Industry development has a technogenic impact on the environment, thereby posing a threat to health and welfare of farm animals. As a result, toxic substances accumulate in soil, water, feed, and have a long period of decomposition. At the same time, changes in the metabolic profile occur in animals, leading to a decrease in their resistance to viral and bacterial infections. The search for new means and methods to stop the development of pathological conditions and create conditions for the resistance of cows to technogenic stress seems to be relevant. In this regard, the purpose was to study the effect of аminoseleferon-B on hematological parameters and protein metabolism of cows with immune deficiency under technogenic load caused by the chemical industry producing mineral fertilizers in Voronezh region. During monitoring soil and water bodies near this object, an excess of the maximum permissible concentrations for heavy metal content was established. The studies were carried out in industrial livestock complex on 20 highly productive dairy cows with a secondary immunodeficiency state, located in the zone of exposure to chemical emissions into the atmosphere. Control and experimental groups of animals were formed. Experimental cows were injected with аminoseleferon-B. It was revealed that the presence of cows in conditions of technogenic impact on the environment leads to decrease in total protein, change in blood fractional composition, which negatively affects physiological processes in the body. Insufficient levels of and -globulin fractions in cow blood indicate inhibition of natural resistance factors. A negative reaction of animal organism associated with exposure to toxins is indicated by significant increase in the level of -globulins in blood. It was found that аminoseleferon-B had a corrective effect on blood morphological parameters and protein metabolism, significantly increasing number of erythrocytes, leukocytes, hemoglobin, lymphocytes, monocytes, total protein, -globulins, -globulins and reducing content of neutrophils, eosinophils, -globulins to normal levels. Thus, аminoseleferon-B contributed to increase in natural resistance, adaptation to adverse environmental factors and stimulation of metabolic processes in cows.
The explosion and collapse of the World Trade Center (WTC) was a catastrophic event that produced an aerosol plume impacting many workers, residents, and commuters during the first few days after 11 September 2001. Three bulk samples of the total settled dust and smoke were collected at weather-protected locations east of the WTC on 16 and 17 September 2001; these samples are representative of the generated material that settled immediately after the explosion and fire and the concurrent collapse of the two structures. We analyzed each sample, not differentiated by particle size, for inorganic and organic composition. In the inorganic analyses, we identified metals, radionuclides, ionic species, asbestos, and inorganic species. In the organic analyses, we identified polycyclic aromatic hydrocarbons (PAHs), polychlorinated biphenyls, polychlorinated dibenzodioxins, polychlorinated dibenzofurans, pesticides, phthalate esters, brominated diphenyl ethers, and other hydrocarbons. Each sample had a basic pH. Asbestos levels ranged from 0.8% to 3.0% of the mass, the PAHs were > 0.1% of the mass, and lead ranged from 101 to 625 microg/g. The content and distribution of material was indicative of a complex mixture of building debris and combustion products in the resulting plume. These three samples were composed primarily of construction materials, soot, paint (leaded and unleaded), and glass fibers (mineral wool and fiberglass). Levels of hydrocarbons indicated unburned or partially burned jet fuel, plastic, cellulose, and other materials that were ignited by the fire. In morphologic analyses we found that a majority of the mass was fibrous and composed of many types of fibers (e.g., mineral wool, fiberglass, asbestos, wood, paper, and cotton). The particles were separated into size classifications by gravimetric and aerodynamic methods. Material 53 microm in diameter. The results obtained from these samples can be used to understand the contact and types of exposures to this unprecedented complex mixture experienced by the surviving residents, commuters, and rescue workers directly affected by the plume from 11 to 12 September and the evaluations of any acute or long-term health effects from resuspendable dust and smoke to the residents, commuters, and local workers, as well as from the materials released after 11 September until the fires were extinguished. Further, these results support the need to have the interior of residences, buildings, and their respective HVAC systems professionally cleaned to reduce long-term residential risks before rehabitation.
The next revolution of industry will turn the industries as well as the entire society into a human-centric shape. The human presence in industrial environment and the human participation in industrial processes will be magnified more than ever before. To cope with the emerging challenges raised by this revolution, 6G ambitions to bridge the three domains of digital information, physical assets and humans into one merged cyber-physical-human world. This proposes not only an unprecedented demand for digital twin solutions, but also new technical requirements. Especially, aiming at a human-centric industrial DT system, novel multi-sensory human-machine interfaces will play a key role in this paradigm shift.
Using state-of-the-art techniques in computer vision, we analyze one million satellite images covering 12% of the African continent between 1984 and 2019 to track local development around 1,658 mineral deposits. We use stacked event studies and difference-in-difference models to estimate the impact of mine openings and closings. The magnitude of the effect of mine openings is considerable - after 15 years, urban areas within 20km of an opening mine almost double in size. We find strong evidence of a political resource curse at the local level. Although mining boosts the local economy in democratic countries, these gains are meager in autocracies and come at the expense of tripling the likelihood of conflict relative to prior the onset of mining. Furthermore, our results suggest that the growth acceleration in mining areas is only temporary and diminishes with the closure of the mine.
We consider the bilateral trade problem, in which two agents trade a single indivisible item. It is known that the only dominant-strategy truthful mechanism is the fixed-price mechanism: given commonly known distributions of the buyer's value $B$ and the seller's value $S$, a price $p$ is offered to both agents and trade occurs if $S \leq p \leq B$. The objective is to maximize either expected welfare $\mathbb{E}[S + (B-S) \mathbf{1}_{S \leq p \leq B}]$ or expected gains from trade $\mathbb{E}[(B-S) \mathbf{1}_{S \leq p \leq B}]$. We improve the approximation ratios for several welfare maximization variants of this problem. When the agents' distributions are identical, we show that the optimal approximation ratio for welfare is $\frac{2+\sqrt{2}}{4}$. With just one prior sample from the common distribution, we show that a $3/4$-approximation to welfare is achievable. When agents' distributions are not required to be identical, we show that a previously best-known $(1-1/e)$-approximation can be strictly improved, but $1-1/e$ is optimal if only the seller's distribution is known.
Abstract Modern living is heavily dependenton mining activities. Having a secure and stable supply of mineral resources has proven to be a key for societies, especially during periods of war. A total of 39 raw materials are identified as ‘strategic’ for the current European defense industry and 16 are additionally considered critical due to economic reasons and risks of supply by the European Commission. Any material can become critical if the demand exceeds supply and this is illustrated through a case study of tin and tungsten demand in Spain during the First World War and Second World War. Tungsten, identified as strategic, was extracted in Spain throughout 20th century, in the process becoming the most important supplier for Germany during Second World War. The extraction of tin has also had political implications, being the basic component used in the manufacturing tin cans. These cases may be used as a proxy for gauging how even a single mineral may boost economies and can be assimilated to current efforts being made across the world to secure supplies of raw materials.
Célestin Coquidé, José Lages, Dima L. Shepelyansky
We present a model of worldwide crisis contagion based on the Google matrix analysis of the world trade network obtained from the UN Comtrade database. The fraction of bankrupted countries exhibits an \textit{on-off} phase transition governed by a bankruptcy threshold $κ$ related to the trade balance of the countries. For $κ>κ_c$, the contagion is circumscribed to less than 10\% of the countries, whereas, for $κ<κ_c$, the crisis is global with about 90\% of the countries going to bankruptcy. We measure the total cost of the crisis during the contagion process. In addition to providing contagion scenarios, our model allows to probe the structural trading dependencies between countries. For different networks extracted from the world trade exchanges of the last two decades, the global crisis comes from the Western world. In particular, the source of the global crisis is systematically the Old Continent and The Americas (mainly US and Mexico). Besides the economy of Australia, those of Asian countries, such as China, India, Indonesia, Malaysia and Thailand, are the last to fall during the contagion. Also, the four BRIC are among the most robust countries to the world trade crisis.
Giuseppe Amato, Malte Behrmann, Frédéric Bimbot
et al.
Thanks to the Big Data revolution and increasing computing capacities, Artificial Intelligence (AI) has made an impressive revival over the past few years and is now omnipresent in both research and industry. The creative sectors have always been early adopters of AI technologies and this continues to be the case. As a matter of fact, recent technological developments keep pushing the boundaries of intelligent systems in creative applications: the critically acclaimed movie "Sunspring", released in 2016, was entirely written by AI technology, and the first-ever Music Album, called "Hello World", produced using AI has been released this year. Simultaneously, the exploratory nature of the creative process is raising important technical challenges for AI such as the ability for AI-powered techniques to be accurate under limited data resources, as opposed to the conventional "Big Data" approach, or the ability to process, analyse and match data from multiple modalities (text, sound, images, etc.) at the same time. The purpose of this white paper is to understand future technological advances in AI and their growing impact on creative industries. This paper addresses the following questions: Where does AI operate in creative Industries? What is its operative role? How will AI transform creative industries in the next ten years? This white paper aims to provide a realistic perspective of the scope of AI actions in creative industries, proposes a vision of how this technology could contribute to research and development works in such context, and identifies research and development challenges.
Neave O'Clery, Samuel Heroy, Francois Hulot
et al.
As early as the 1920's Marshall suggested that firms co-locate in cities to reduce the costs of moving goods, people, and ideas. These 'forces of agglomeration' have given rise, for example, to the high tech clusters of San Francisco and Boston, and the automobile cluster in Detroit. Yet, despite its importance for city planners and industrial policy-makers, until recently there has been little success in estimating the relative importance of each Marshallian channel to the location decisions of firms. Here we explore a burgeoning literature that aims to exploit the co-location patterns of industries in cities in order to disentangle the relationship between industry co-agglomeration and customer/supplier, labour and idea sharing. Building on previous approaches that focus on across- and between-industry estimates, we propose a network-based method to estimate the relative importance of each Marshallian channel at a meso scale. Specifically, we use a community detection technique to construct a hierarchical decomposition of the full set of industries into clusters based on co-agglomeration patterns, and show that these industry clusters exhibit distinct patterns in terms of their relative reliance on individual Marshallian channels.